Buy

Purchase Options

Share

advertisement

Getting more value from knowledge — especially from a firm’s own hard-won knowledge — is one of the central challenges facing companies today. Many organizations have approached this problem in recent years by making big investments in IT systems, especially content repositories and databases. For example, 70% of organizations with more than 10,000 employees have more than 100 separate content repositories.1 Despite such investments, many companies have not seen much in the way of returns.

A particularly egregious example is a Fortune 50 manufacturing firm that put more than 3 million documents, previously dispersed in more than 2,000 systems, into one database. In the first three years alone, the project’s budget came to more than $22 million. Unfortunately, the system mostly created confusion, as no changes were made in the way documents were presented to employees or to help them navigate the new system. The anticipated benefits from the substantial investment went largely unrealized.

As bad as this story sounds, it is not uncommon. A research report by analysts at International Data Group’s IDC estimated that an organization employing 1,000 knowledge workers might easily incur a cost of more than $6 million per year in lost productivity as employees fail to find existing knowledge they need, waste time searching for nonexistent knowledge and recreate knowledge that is available but could not be located. Imagine the impact on an organization with 50,000 or more employees.

The challenge in reducing such waste and increasing productivity is to help employees find what they need, when they need it. The good news is that companies can easily do better than to employ the blunt tools they have used so far, and they can do so with incremental investments. A good place to start is by considering how the innovative giants of the Internet — Google, eBay and Amazon.com — have built business models around attracting and retaining customers. A big part of their success has come from their ability to make it easy for customers to find what they are looking for, to browse for products and services, and to evaluate potential purchases.

Member

Subscriber

About the Authors

Leigh M. Weiss and Marla M. Capozzi are consultants with McKinsey & Co. in Boston.Laurence Prusak is a Boston-based consultant and the co-author of What’s the Big Idea? Creating and Capitalizing on the Best Management Thinking (Harvard Business School Press, 2003). They can be reached at Leigh_Weiss@McKinsey.com, Marla_ Capozzi@McKinsey.com and lprusak@msn.com.

2. Many approaches to creating more value from knowledge have been addressed in the management and academic literature. These include transferring and applying tacit knowledge and expertise; acquiring, creating and codifying new knowledge; and organizing existing knowledge, both tacit and codified. We focus on a subset of these issues — knowledge that has already been codified and placed in a repository. This knowledge represents significant sunk costs by organizations that we believe could be made much more valuable with incremental investments. The management of codified knowledge has been discussed in M. Zack, “Managing Codified Knowledge,” Sloan Management Review 40 (summer 1999): 45–58; R. Cowan, P.A. David and D. Foray, “The Explicit Economics of Knowledge Codification and Tacitness,” Industrial and Corporate Change 9 (2000): 211–253; and R. Cowan and D. Foray, “The Economics of Codification and the Diffusion of Knowledge,” Industrial and Corporate Change 6 (1997): 595–622. However, little attention has been given to the relationship between codified knowledge and knowledge-worker productivity in particular and to illustrating by analogy the ways in which nonintuitive case studies have relevance for managers trying to increase the value of their organizations’ documents.

3. An implicit assumption is that existing documents represent some or most of the codified knowledge a company would want employees to find and apply. If this were not the case, organizations would want to devote more time to identifying, codifying and prioritizing the most important knowledge.

4. These actions build on the significant contributions in the literature to the design of information- and knowledge-based products, including M.H. Meyer and M. Zack, “The Design of Information Products,” Sloan Management Review 37 (spring 1996): 43–59; and the more popular views of information design by E. Tufte (all published by Graphics Press, Cheshire, Connecticut): “The Visual Display of Quantitative Information” (2001), “Visual and Statistical Thinking: Displays of Evidence for Decision-Making” (1997), and “Envisioning Information” (1990).

6. EBay is similarly successful helping customers qualify potential sellers, which is critical given that their business model is based on trust. Every eBay member has a profile with basic information about the member and a list of feedback left by their trading partners from previous transactions. Learning to trust a potential seller (or buyer) has a lot to do with what their past customers or sellers have said about them. For each transaction, only the buyer and seller can rate each other by leaving feedback, which consists of a positive, negative or neutral rating and a short comment. The feedback gives other eBay shoppers and sellers a good idea of what to expect when dealing with that person.

7. Consider an example: If average employee salaries are $80,000 and an employee searches for knowledge on average twice daily, then a five-minute savings in search time could result in 40 hours of time saved over the course of a year per employee (assuming 240 working days). This represents over $15 million for an employee base of 10,000 workers and 400,000 hours of time that could be better spent on more productive activities than searching for knowledge.